%0 Conference Proceedings %T Monash University’s Submissions to the WNGT 2019 Document Translation Task %A Maruf, Sameen %A Haffari, Gholamreza %Y Birch, Alexandra %Y Finch, Andrew %Y Hayashi, Hiroaki %Y Konstas, Ioannis %Y Luong, Thang %Y Neubig, Graham %Y Oda, Yusuke %Y Sudoh, Katsuhito %S Proceedings of the 3rd Workshop on Neural Generation and Translation %D 2019 %8 November %I Association for Computational Linguistics %C Hong Kong %F maruf-haffari-2019-monash %X We describe the work of Monash University for the shared task of Rotowire document translation organised by the 3rd Workshop on Neural Generation and Translation (WNGT 2019). We submitted systems for both directions of the English-German language pair. Our main focus is on employing an established document-level neural machine translation model for this task. We achieve a BLEU score of 39.83 (41.46 BLEU per WNGT evaluation) for En-De and 45.06 (47.39 BLEU per WNGT evaluation) for De-En translation directions on the Rotowire test set. All experiments conducted in the process are also described. %R 10.18653/v1/D19-5628 %U https://aclanthology.org/D19-5628 %U https://doi.org/10.18653/v1/D19-5628 %P 256-261